Lianhui Zheng
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Lianhui Zheng has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Han Yang
Practice Division of the Academic Affairs Office, Sanming University, Sanming 365004, China
1 shared publication - Rui Ge Zhang
College of Mechanical and Electrical Engineering, Sanming University, Sanming 365004, China
1 shared publication - Yao Li
College of Mechanical and Electrical Engineering, Sanming University, Sanming 365004, China
1 shared publication - Yuwei Cai
College of Mechanical and Electrical Engineering, Sanming University, Sanming 365004, China
1 shared publication - Zhongjian Gao
College of Mechanical and Electrical Engineering, Sanming University, Sanming 365004, China
1 shared publication
Latest Publications
- Open Access
- 6 August 2026
- Published by MDPI AG in Future Internet
- Vol. 18 (8) , 417
Wi-CSNet: A Spatio-Temporal Model for CSI-Based Human Activity Recognition
Human Activity Recognition (HAR) based on Channel State Information (CSI) has attracted considerable attention as a privacy-preserving sensing paradigm. However, CSI-based HAR faces several challenges, including environmental noise, long-range temporal dependencies, and the anisotropic structure of CSI tensors. To address these challenges, this paper presents Wi-CSNet, a lightweight CSI-oriented framework that integrates Discrete Wavelet Transform (DWT) preprocessing, asymmetric-stride convolutions, and a Cross-Scanning State Space Duality (CS-SSD) block derived from Mamba2. DWT preprocessing compresses temporal signals while preserving motion-related trends and reducing input dimensionality. Asymmetric-stride convolutions balance feature scales across heterogeneous CSI dimensions, while the lightweight CS-SSD module captures global dependencies with only a 0.63% parameter overhead. Extensive experiments demonstrate that Wi-CSNet achieves accuracies of 97.81% on HHI, 99.92% on UT-HAR, and 100% on NTU-HAR. These results confirm the effectiveness and robustness of Wi-CSNet for fine-grained CSI-based activity recognition in complex environments.
- 6 August 2026
- Published by MDPI AG in Future Internet
- Vol. 18 (8) , 417
Open AccessWi-CSNet: A Spatio-Temporal Model for CSI-Based Human Activity Recognition
Human Activity Recognition (HAR) based on Channel State Information (CSI) has attracted considerable attention as a privacy-preserving sensing paradigm. However, CSI-based HAR faces several challenges, including environmental noise, long-range temporal dependencies, and the anisotropic structure of CSI tensors. To address these challenges, this paper presents Wi-CSNet, a lightweight CSI-oriented framework that integrates Discrete Wavelet Transform (DWT) preprocessing, asymmetric-stride convolutions, and a Cross-Scanning State Space Duality (CS-SSD) block derived from Mamba2. DWT preprocessing compresses temporal signals while preserving motion-related trends and reducing input dimensionality. Asymmetric-stride convolutions balance feature scales across heterogeneous CSI dimensions, while the lightweight CS-SSD module captures global dependencies with only a 0.63% parameter overhead. Extensive experiments demonstrate that Wi-CSNet achieves accuracies of 97.81% on HHI, 99.92% on UT-HAR, and 100% on NTU-HAR. These results confirm the effectiveness and robustness of Wi-CSNet for fine-grained CSI-based activity recognition in complex environments.